scholarly journals Impact of Income Inequality on Urban Air Quality: A Game Theoretical and Empirical Study in China

2021 ◽  
Vol 18 (16) ◽  
pp. 8546
Author(s):  
Feng Wang ◽  
Jian Yang ◽  
Joshua Shackman ◽  
Xin Liu
Keyword(s):  
Air Quality ◽  
Income Inequality ◽  
Empirical Study ◽  
Environmental Pollution ◽  
Environmental Protection ◽  
Clean Energy ◽  
Quality Data ◽  
Urban Air ◽  
Coal Consumption ◽  
The Impact

Income inequality and environmental pollution are of great concern in China. It is important to better understand whether the narrowing of income inequality and environmental improvement contradict each other. The study aims to investigate the linkage between income inequality and environmental pollution. To illustrate the interplay between different income groups on environmental issues, we apply a mixed-strategy game. Based on the game-theoretic analytical result, the probability of residents supporting clean energy and environmental protection decreases as income inequality widens and increases as inequality narrows. This empirical study is based on the proportion of coal consumption and urban air pollution data from 113 key environmental protection cities and regions in China. The air quality data are from the National Environmental Air Quality Monitoring Network published in the China Statistical Yearbook from 2014–2018. Convincing results show that regions with higher income inequality suffer severe smog and related pollution and that economies with narrow income disparity experience significant improvements in smog and pollution control, with the expansion of the proportion of clean energy use. The results also provide no evidence of the impact of per capita income on pollution. We studied the relationship between individuals of different wealth levels within an economy, within a repeated-game setting. The finding suggests that the distribution of growth impacts pollution. Imposing higher taxes on air polluters while transferring the revenue to the lower-income group is suggested.

scholarly journals Prediction of Environmental Pollution Using Hybrid PSO-K-Means Approach

2021 ◽  
Vol 12 (2) ◽  
pp. 65-76
Author(s):  
Manish Mahajan ◽  
Santosh Kumar ◽  
Bhasker Pant
Keyword(s):  
Air Quality ◽  
Environmental Pollution ◽  
Productivity Loss ◽  
Hybrid Approach ◽  
Quality Data ◽  
Quality Prediction ◽  
Clustering Methods ◽  
Air Quality Prediction ◽  
The Impact

Air pollution is increasing day by day, decreasing the world economy, degrading the quality of life, and resulting in a major productivity loss. At present, this is one of the most critical problems. It has a significant impact on human health and ecosystem. Reliable air quality prediction can reduce the impact it has on the nearby population and ecosystem; hence, improving air quality prediction is the prime objective for the society. The air quality data collected from sensors usually contains deviant values called outliers which have a significant detrimental effect on the quality of prediction and need to be detected and eliminated prior to decision making. The effectiveness of the outlier detection method and the clustering methods in turn depends on the effective and efficient choice of parameters like initial centroids and number of clusters, etc. The authors have explored the hybrid approach combining k-means clustering optimized with particle swarm optimization (PSO) to optimize the cluster formation, thereby improving the efficiency of the prediction of the environmental pollution.

scholarly journals Association of temporary Environmental Protection Agency regulation suspension with industrial economic viability and local air quality in California, United States

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Emily Chang ◽  
Kenneth Zhang ◽  
Margaret Paczkowski ◽  
Sara Kohler ◽  
Marco Ribeiro
Keyword(s):  
United States ◽  
Air Quality ◽  
Environmental Protection ◽  
Environmental Protection Agency ◽  
Manufacturing Industry ◽  
Economic Viability ◽  
Treatment Control ◽  
Oil Refineries ◽  
Pollution Levels ◽  
The Impact

Abstract Background This study seeks to answer two questions about the impacts of the 2020 Environmental Protection Agency’s enforcement regulation rollbacks: is this suspension bolstering the economic viability of industries as oil and manufacturing executives claim they will and are these regulations upholding the agency’s mission of protecting the environment? Results To answer the former question, we utilized 6 months of state employment level data from California, United States, as a method of gauging the economic health of agency-regulated industries. We implemented a machine learning model to predict weekly employment data and a t-test to indicate any significant changes in employment. We found that, following California's state-issued stay-at-home order and the agency’s regulation suspension, oil and certain manufacturing industries had statistically significant lower employment values. To answer the latter question, we used 10 years of PM2.5 levels in California, United States, as a metric for local air quality and treatment–control county pairs to isolate the impact of regulation rollbacks from the impacts of the state lockdown. Using the agency’s data, we performed a t-test to determine whether treatment–control county pairs experienced a significant change in PM2.5 levels. Even with the statewide lockdown—a measure we hypothesized would correlate with decreased mobility and pollution levels—in place, counties with oil refineries experienced the same air pollution levels when compared to historical data averaged from the years 2009 to 2019. Conclusions In contrast to the expectation that the suspension would improve the financial health of the oil and manufacturing industry, we can conclude that these industries are not witnessing economic growth with the suspension and state shutdown in place. Additionally, counties with oil refineries could be taking advantage of these rollbacks to continue emitting the same amount of PM2.5, in spite of state lockdowns. For these reasons, we ask international policymakers to reconsider the suspension of enforcement regulations as these actions do not fulfill their initial expectations. We recommend the creation and maintenance of pollution control and prevention programs that develop emission baselines, mandate the construction of pollution databases, and update records of pollution emissions.

aiRe - A web-based R application for simple, accessible and repeatable analysis of urban air quality data

2021 ◽  
Vol 138 ◽  
pp. 104976
Author(s):  
Juan José Díaz ◽  
Ivan Mura ◽  
Juan Felipe Franco ◽  
Raha Akhavan-Tabatabaei
Keyword(s):  
Air Quality ◽  
Urban Air Quality ◽  
Quality Data ◽  
Urban Air ◽  
Web Based ◽  
Air Quality Data

scholarly journals Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

2021 ◽  
Author(s):  
Shwet Ketu ◽  
Pramod Kumar Mishra
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Class Imbalance ◽  
Imbalanced Data ◽  
Classification Algorithm ◽  
Quality Data ◽  
Pollution Level ◽  
Classification Problems ◽  
Chi Square ◽  
The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

Assessing the impact of the New Athens airport to urban air quality with contemporary air pollution models

1997 ◽  
Vol 31 (10) ◽  
pp. 1497-1511 ◽  
Author(s):  
N. Moussiopoulos ◽  
P. Sahm ◽  
K. Karatzas ◽  
S. Papalexiou ◽  
A. Karagiannidis
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Air Quality ◽  
Urban Air ◽  
The Impact ◽  
Air Pollution Models

Impacts on Energy and Environmental Efficiency by Media Report – Modifies Undesirable Dynamic DEA

2020 ◽  
Author(s):  
Ying Li ◽  
Tai-Yu Lin ◽  
Yung-ho Chiu ◽  
Huaming Chen ◽  
Hongyi Cen
Keyword(s):  
Economic Growth ◽  
Air Quality ◽  
Environmental Pollution ◽  
Environmental Protection ◽  
News Media ◽  
Media Coverage ◽  
Quality Index ◽  
Environmental Efficiency ◽  
Air Quality Index ◽  
Media Reports

Abstract Background: Rapid economic growth in China has resulted in a commensurate increase in energy consumption, which in turn has caused an increase in environmental pollution problems. Past research has mainly focused on energy and environmental efficiency analyses with little consideration of the influence of media influence on environmental protection. Further, most studies have used static models and have ignored the dynamic changes over time. Methods : To go some way to filling this research gap, this study developed a modified undesirable Dynamic DEA model that included air quality index (AQI) and CO2 indicators to explore the relationship between energy, the environment and media efficiency in 31 Chinese cities from 2013 to 2016. Results: It was found that: 1. Chongqing, Guangzhou, Nanjing and Shanghai had efficiencies of 1, but Lanzhou, Shijiazhuang, Taiyuan, Xining and Yinchuan needed significant improvements; 2. while Chongqing, Guangzhou, Kunming, Nanning and Shanghai had relatively high media efficiency, the other cities had low efficiency and required improvements; 3. the CO 2 emissions efficiency in most cities was better than the air quality index efficiency; and 4. media reports in most cities were found to have a more positive impact on CO 2 emissions efficiency than AQI efficiency. Conclusions: As environmental awareness enhances the health of civilians and promotes economic growth, the news media needs to promote environmental protection, and should increase its environmental pollution coverage. The quality of media reports on environmental pollution and especially on air pollution need to be improved. Therefore, environmental pollution and awareness media coverage needs to be increased.

scholarly journals Citizen as Sensors' Commitment in Urban Public Action

2019 ◽  
Vol 8 (4) ◽  
pp. 42-59 ◽  
Author(s):  
Gwendoline l'Her ◽  
Myriam Servières ◽  
Daniel Siret
Keyword(s):  
Air Quality ◽  
Citizen Science ◽  
Urban Air Quality ◽  
Urban Air ◽  
The Public ◽  
Public Action ◽  
Quality Issue ◽  
Data Analyses ◽  
The Impact

Based on a case study in Rennes, the article presents how a group of urban public actors re-uses methods and technology from citizen sciences to raise the urban air quality issue in the public debate. The project gives a group of inhabitants the opportunity to follow air quality training and proceed PM2.5µm measurements. The authors question the impact of the ongoing hybridisation between citizen science and urban public action on participants' commitment. The authors present how the use of PM2.5-sensors during 11 weeks led to a disengagement phenomenon, even if the authors observe a strong participation to workshops. These results come from an interdisciplinary methodology using observations, interviews, and data analyses.

scholarly journals Positive effects of COVID-19 lockdown on air quality of industrial cities (Ankleshwar and Vapi) of Western India

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ritwik Nigam ◽  
Kanvi Pandya ◽  
Alvarinho J. Luis ◽  
Raja Sengupta ◽  
Mahender Kotha
Keyword(s):  
Air Quality ◽  
Meta Analysis ◽  
Linear Regression Analysis ◽  
Quality Data ◽  
Western India ◽  
Rapid Reduction ◽  
Positive Effects ◽  
Pollutant Concentrations ◽  
The Impact

AbstractOn January 30, 2020, India recorded its first COVID-19 positive case in Kerala, which was followed by a nationwide lockdown extended in four different phases from 25th March to 31st May, 2020, and an unlock period thereafter. The lockdown has led to colossal economic loss to India; however, it has come as a respite to the environment. Utilizing the air quality index (AQI) data recorded during this adverse time, the present study is undertaken to assess the impact of lockdown on the air quality of Ankleshwar and Vapi, Gujarat, India. The AQI data obtained from the Central Pollution Control Board was assessed for four lockdown phases. We compared air quality data for the unlock phase with a coinciding period in 2019 to determine the changes in pollutant concentrations during the lockdown, analyzing daily AQI data for six pollutants (PM10, PM2.5, CO, NO2, O3, and SO2). A meta-analysis of continuous data was performed to determine the mean and standard deviation of each lockdown phase, and their differences were computed in percentage in comparison to 2019; along with the linear correlation analysis and linear regression analysis to determine the relationship among the air pollutants and their trend for the lockdown days. The results revealed different patterns of gradual to a rapid reduction in most of the pollutant concentrations (PM10, PM2.5, CO, SO2), and an increment in ozone concentration was observed due to a drastic reduction in NO2 by 80.18%. Later, increases in other pollutants were also observed as the restrictions were eased during phase-4 and unlock 1. The comparison between the two cities found that factors like distance from the Arabian coast and different industrial setups played a vital role in different emission trends.

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